Designing laboratory wind simulations using artificial neural network

Kozmar, Hrvoje and Križan, Josip and Gašparac, Goran and Antonić, Oleg and Grisogono, Branko (2015) Designing laboratory wind simulations using artificial neural network. = Designing laboratory wind simulations using artificial neural networks. Theoretical and Applied Climatology, 120 (3/4). pp. 723-736. ISSN 0177-798X. Vrsta rada: ["eprint_fieldopt_article_type_article" not defined]. Kvartili JCR: Q2 (2015). Točan broj autora: 5.

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While experiments in boundary layer wind tunnels remain to be a major research tool in wind engineering and environmental aerodynamics, designing the modeling hardware required for a proper atmospheric boundary layer (ABL) simulation can be costly and time consuming. Hence, possibilities are sought to speed-up this process and make it more time-efficient. In this study, two artificial neural networks (ANNs) are developed to determine an optimal design of the Counihan hardware, i.e., castellated barrier wall, vortex generators, and surface roughness, in order to simulate the ABL flow developing above urban, suburban, and rural terrains, as previous ANN models were created for one terrain type only. A standard procedure is used in developing those two ANNs in order to further enhance best-practice possibilities rather than to improve existing ANN designing methodology. In total, experimental results obtained using 23 different hardware setups are used when creating ANNs. In those tests, basic barrier height, barrier castellation height, spacing density, and height of surface roughness elements are the parameters that were varied to create satisfactory ABL simulations. The first ANN was used for the estimation of mean wind velocity, turbulent Reynolds stress, turbulence intensity, and length scales, while the second one was used for the estimation of the power spectral density of velocity fluctuations. This extensive set of studied flow and turbulence parameters is unmatched in comparison to the previous relevant studies, as it includes here turbulence intensity and power spectral density of velocity fluctuations in all three directions, as well as the Reynolds stress profiles and turbulence length scales. Modeling results agree well with experiments for all terrain types, particularly in the lower ABL within the height range of the most engineering structures, while exhibiting sensitivity to abrupt changes and data scattering in profiles of wind-tunnel results. The proposed approach allows for quicker and more effective achieving targeted flow and turbulence features of the ABL wind-tunnel simulations as compared to the common trial and error procedures. This methodology is expected to enable wind-tunnel modelers a quick and time-efficient designing of ABL simulations in studies dealing with air pollutant dispersion, wind loading of structures, wind energy, and urban micrometeorology, where atmospheric flow and turbulence play a key role. © 2014 Springer-Verlag Wien.

Item Type: Article (["eprint_fieldopt_article_type_article" not defined])
Keywords (Croatian): Atmospheric boundary layer; wind-tunnel simulation; experimental hardware design; artificial neural networks
Subjects: TECHNICAL SCIENCE > Geodesy
TECHNICAL SCIENCE > Civil engineering
TECHNICAL SCIENCE > Mechanical Engineering
Divisions: 1400 Department of fluid mechanics > 1420 Chair of environment and construction aerodynamics
Indexed in Web of Science: Yes
Indexed in Current Contents: Yes
Quartiles: Q2 (2015)
Date Deposited: 02 Jun 2015 12:53
Last Modified: 22 Aug 2017 11:03

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